Python utils.write_data() Examples
The following are 9
code examples of utils.write_data().
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Example #1
| Source File: run_lfads.py From DOTA_models with Apache License 2.0 | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
Example #2
| Source File: run_lfads.py From yolo_v2 with Apache License 2.0 | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
Example #3
| Source File: run_lfads.py From Gun-Detector with Apache License 2.0 | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
Example #4
| Source File: run_lfads.py From hands-detection with MIT License | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
Example #5
| Source File: run_lfads.py From object_detection_kitti with Apache License 2.0 | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
Example #6
| Source File: run_lfads.py From object_detection_with_tensorflow with MIT License | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
Example #7
| Source File: run_lfads.py From g-tensorflow-models with Apache License 2.0 | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
Example #8
| Source File: run_lfads.py From models with Apache License 2.0 | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
Example #9
| Source File: run_lfads.py From multilabel-image-classification-tensorflow with MIT License | 6 votes |
|
def write_model_parameters(hps, output_fname=None, datasets=None):
"""Save all the model parameters
Save all the parameters to hps.lfads_save_dir.
Args:
hps: The dictionary of hyperparameters.
output_fname: The prefix of the file in which to save the generated
samples.
datasets: A dictionary of data dictionaries. The dataset dict is simply a
name(string)-> data dictionary mapping (See top of lfads.py).
"""
if not output_fname:
output_fname = "model_params"
else:
output_fname = output_fname + "_model_params"
fname = os.path.join(hps.lfads_save_dir, output_fname)
print("Writing model parameters to: ", fname)
# save the optimizer params as well
model = build_model(hps, kind="write_model_params", datasets=datasets)
model_params = model.eval_model_parameters(use_nested=False,
include_strs="LFADS")
utils.write_data(fname, model_params, compression=None)
print("Done.")
